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We can consider openness to other, different pictures of complexity and other perspectives on complexity important as a test of one's own picture: is our picture of complex reality robust when we compare it to other pictures, can we learn from other pictures and do we pass the test of being criticized by others about the robustness of our picture?
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Therefore, the resulting data set might provide a biased picture of complexity.
Our findings contribute to the emerging picture of complexity in phylogeographic histories and of responses to Pleistocene glaciations across species and regions globally.
This could increase the impression of complexity, particularly in line-drawn pictures with many lines (e.g., the train).
This task requires the selection of a target picture out of four presented pictures of varying complexity after auditory prompting.
The generalization of the use of such arrays should provide unbiased and high-quality pictures of the complexity and the dynamics of transcriptional landscapes (Xu et al., 2009).
Mapping results onto known biochemical pathways informs interpretation but can also give a humbling picture of the complexity of real-life metabolic networks.
It appears that the real picture of the complexity of phosphorelay signal transduction in prokaryotes is only beginning to unfold.
Finally, we also present algorithms for reasoning under probabilistic entailment in System Z and probabilistic lexicographic entailment, and we give a precise picture of its complexity.
In particular, we give a precise picture of the complexity of deciding explanations, α-partial explanations, and partial explanations, and of computing the explanatory power of partial explanations.
In this paper, we fill these gaps and first draw a precise picture of the complexity of default reasoning from conditional knowledge bases: Given a conditional knowledge base KB and a default φ→ψ, does KB entail φ→ψ?
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